Abstract
Maritime transportation has generated a considerable amount of emissions and affected the global atmospheric environment. A key step of effective emission control is to construct reliable models of emission accounting. In recent years, there has been a major innovation in emission accounting, the application of big data, especially the data extracted from automatic identification system (AIS). In this paper, a dynamic and comprehensive analysis is developed to depict how emission accounting models have been evolved in this era of big data. In the perspective-based review, we thoroughly investigate the geographical coverage and pollutant types involved in the existing emission studies. In the process-based review, this paper establishes a solid knowledge framework of the two basic modelling concepts: top-down and bottom-up approaches. Furthermore, updated emission modelling methodologies and high resolute data sources are introduced. But the latest models are still subject to various sources of uncertainties. Hence, this paper identifies such unsolved problems and sets up a future research agenda.
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